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Record W4211215745 · doi:10.32920/ryerson.14655969.v1

Hybridizing nickel platform using ultra-short pulsed laser: a new paradigm towards biomedical sensing and theranostics

2021· preprint· en· W4211215745 on OpenAlexaff
Sivaprasad Chinnakkannu Vijayakumar

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicLaser-Ablation Synthesis of Nanoparticles
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsHeLaBiosensorCancer cellNanotechnologyBiomoleculeBiophysicsChemistryBiocompatibilityFluorescenceFibroblastExtracellular matrixMaterials scienceCellCancerBiochemistryIn vitroBiology

Abstract

fetched live from OpenAlex

A self-assembled 3D nanonetwork of Nickel and Nickel Oxide is synthesized by ultrashort pulsed laser through multiphoton ionization. The synthesized nanonetwork with tunable physiochemical property was investigated for cancer therapeutic and biomolecular sensing applications. In this thesis, the developed 3D nickel nanomatrix effectively regulated HeLa cancer cell adhesion and proliferation mimicking Extracellular Matrix (ECM). This behaviour explicitly demonstrated that the initial incubation period was devoted to baiting fibroblast and HeLa cells to proliferate upon the nanomatrix and subsequently the same nanomatrix exhibited cell trapping behaviour upon HeLa cells after an increased incubation period thereby controlling proliferation. The results brought new insight as to how HeLa cells behaved differently when compared to NIH3T3 fibroblast cells opening pioneering application in drug-free cancer therapy. To delve deeper into nickel nanonetwork for cancer therapy the laser ionization was manipulated to induce two distinct quantum theranosomes. Presently, quantum materials are limited due to 0D & 1D materials lacking biocompatibility resulting in coated materials with labelled tags for fluorescence excitation. The theranosomes mimicked tumor microenvironment by selectively accelerating the proliferation of mammalian fibroblasts cells while inducing cancer therapy. Furthermore, the theranosomes opened up label-free bioimaging probe for differentiating (HeLa & MDAMB-231) from mammalian fibroblast cells for cancer diagnostics. In-addition to label-free bioimaging, the development of an ultrasensitive biosensor for targeted biomolecule sensing was developed addressing the drawback faced with fluorescence imaging using Surface Enhanced Raman Scattering (SERS). We developed a SERS active nano-biosensor to detect chemical dye Crystal Violet (CV) and biomolecule glutathione(GSH). The Raman detection of crystal violet (CV) and glutathione (GSH) molecules was noted with 1 pM (1×10-12M) concentrations at (532 & 785nm) excitation wavelengths with an enhancement factor of 109, not been observed even in plasmonic materials. This extends the limit of detection (LOD), confirming suitability for chemical and biomolecular sensing. Additionally, the quantum confinement effect will result in an ultrasensitive sensor diagnosing and differentiating cancer cells from fibroblast cells. Based on the results in this thesis, the multifunctional feasibility of nano and quantum scale nickel structures arranged in 3D assembly for its direct application in cancer therapeutics, encompassing cancer bioimaging and diagnostics.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.260
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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